Many companies and other organizations operate computer networks that interconnect numerous computing systems to support their operations, such as with the computing systems being co-located (e.g., as part of a local network) or instead located in multiple distinct geographical locations (e.g., connected via one or more private or public intermediate networks). For example, data centers housing significant numbers of interconnected computing systems have become commonplace, such as private data centers that are operated by and on behalf of a single organization, and public data centers that are operated by entities as businesses to provide computing resources to customers. Some public data center operators provide network access, power, and secure installation facilities for hardware owned by various customers, while other public data center operators provide “full service” facilities that also include hardware resources made available for use by their customers.
The advent of virtualization technologies for commodity hardware has provided benefits with respect to managing large-scale computing resources for many customers with diverse needs, allowing various computing resources to be efficiently and securely shared by multiple customers. For example, virtualization technologies may allow a single physical computing machine to be shared among multiple users by providing each user with one or more virtual machines hosted by the single physical computing machine. Each such virtual machine can be thought of as a software simulation acting as a distinct logical computing system that provides users with the illusion that they are the sole operators and administrators of a given hardware computing resource, while also providing application isolation among the various virtual machines.
In addition to providing virtualized compute servers, many network operators have implemented a variety of virtualized storage services with different types of access interfaces, different performance and cost profiles, and the like. For example, some storage services may offer block-level programmatic interfaces, while other storage services may enable clients to use HTTP (HyperText Transfer Protocol) or its variants to access storage objects. Some of the services may utilize primarily magnetic disk-based storage devices, while others may also or instead use solid-state drives (SSDs). Different levels of data durability, availability, and fault-tolerance may be achieved using different storage services. In at least some provider network environments, a variety of storage device types supported by the different storage services may be used for different objects of a given file system. Control-plane components of such file system implementations may have to solve the non-trivial optimization problem of determining how various file system objects should be placed and transferred among the different storage tiers in view of client goals for performance, availability, durability and cost.
While embodiments are described herein by way of example for several embodiments and illustrative drawings, those skilled in the art will recognize that embodiments are not limited to the embodiments or drawings described. It should be understood, that the drawings and detailed description thereto are not intended to limit embodiments to the particular form disclosed, but on the contrary, the intention is to cover all modifications, equivalents and alternatives falling within the spirit and scope as defined by the appended claims. The headings used herein are for organizational purposes only and are not meant to be used to limit the scope of the description or the claims. As used throughout this application, the word “may” is used in a permissive sense (i.e., meaning having the potential to), rather than the mandatory sense (i.e., meaning must). Similarly, the words “include,” “including,” and “includes” mean including, but not limited to.